mirror of
https://gitee.com/fastnlp/fastNLP.git
synced 2024-11-29 18:59:01 +08:00
102 lines
4.5 KiB
Plaintext
102 lines
4.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"'应当为一个字符串，其值应当为以下之一：``[None, \"dist\", \"unrepeatdist\"]``；为 ``None`` 时，表示不需要考虑当前 ``dataloader`` 切换为分布式状态；为 ``\"dist\"`` 时，表示该 ``dataloader`` 应该保证每个 ``gpu`` 上返回的 ``batch`` 的数量是一样多的，允许出现少量 ``sample`` ，在 不同 ``gpu`` 上出现重复；为 ``\"unrepeatdist\"`` 时，表示该 ``dataloader`` 应该保证所有 ``gpu`` 上迭代出来的数据合并起来应该刚好等于原始的 数据，允许不同 ``gpu`` 上 ``batch`` 的数量不一致。其中 ``trainer`` 中 ``kwargs`` 的参数 ``use_dist_sampler`` 为 ``True`` 时，该值为 ``\"dist\"``； 否则为 ``None`` ，``evaluator`` 中的 ``kwargs`` 的参数 ``use_dist_sampler`` 为 ``True`` 时，该值为 ``\"unrepeatdist\"``，否则为 ``None``； 注意当 ``dist`` 为 ``ReproducibleSampler, ReproducibleBatchSampler`` 时，是断点重训加载时 ``driver.load`` 函数在调用； 当 ``dist`` 为 ``str`` 或者 ``None`` 时，是 ``trainer`` 在初始化时调用该函数；'"
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]
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},
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"execution_count": 20,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import re\n",
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"import sys\n",
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"sys.path.append(\"../\")\n",
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"# import fastNLP\n",
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"\n",
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"def get_class(text):\n",
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" return f\":class:`~{text}`\"\n",
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"\n",
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"def get_meth(text):\n",
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" return f\":meth:`~{text}`\"\n",
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"\n",
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"def get_module(text):\n",
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" return f\":mod:`~{text}`\"\n",
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"\n",
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"def replace(matched):\n",
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" \"\"\"\n",
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" \"\"\"\n",
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" text = matched.group()\n",
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" non_space = text.strip()\n",
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" if non_space == \"\":\n",
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" return text\n",
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" # 如果原本就添加了 `，那么只加一个\n",
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" if non_space.startswith(\"`\"):\n",
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" res = \"`\" + non_space\n",
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" else:\n",
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" res = \"``\" + non_space\n",
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" if non_space.endswith(\"`\"):\n",
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" res += \"`\"\n",
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" else:\n",
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" res += \"``\"\n",
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" return text.replace(non_space, f\"{res}\")\n",
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"\n",
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"def transfer(text):\n",
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" \"\"\"\n",
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" 将输入的 ``text`` 中的英文单词添加 \"``\"。在得到结果后最好手动检查一下，\n",
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" \"\"\"\n",
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" res = re.sub(\n",
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" # 匹配字母、下划线、点、逗号、引号、中括号和`\n",
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" pattern=r\"[a-zA-Z_ \\.,\\\"\\'\\[\\]`]+\",\n",
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" repl=replace,\n",
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" string=text\n",
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" )\n",
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" return res\n",
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"\n",
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"\n",
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"text = '应当为一个字符串，其值应当为以下之一：[None, \"dist\", \"unrepeatdist\"]；为 None 时，表示不需要考虑当前 dataloader \\\n",
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" 切换为分布式状态；为 \"dist\" 时，表示该 dataloader 应该保证每个 gpu 上返回的 batch 的数量是一样多的，允许出现少量 sample ，在 \\\n",
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" 不同 gpu 上出现重复；为 \"unrepeatdist\" 时，表示该 dataloader 应该保证所有 gpu 上迭代出来的数据合并起来应该刚好等于原始的 \\\n",
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" 数据，允许不同 gpu 上 batch 的数量不一致。其中 trainer 中 kwargs 的参数 `use_dist_sampler` 为 True 时，该值为 \"dist\"； \\\n",
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" 否则为 None ，evaluator 中的 kwargs 的参数 `use_dist_sampler` 为 True 时，该值为 \"unrepeatdist\"，否则为 None； \\\n",
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" 注意当 dist 为 ReproducibleSampler, ReproducibleBatchSampler 时，是断点重训加载时 driver.load 函数在调用； \\\n",
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" 当 dist 为 str 或者 None 时，是 trainer 在初始化时调用该函数；'\n",
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"transfer(text)"
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]
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}
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],
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"metadata": {
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"interpreter": {
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"hash": "c79c3370938623706c2d55a7989cf7c7c31ff0346157477d22565bb370580b77"
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},
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"kernelspec": {
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"display_name": "Python 3.7.13 ('fnlp')",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.13"
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},
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"orig_nbformat": 4
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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